Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System

Leonidas Tsiopoulos; Alar Kuusik; Jüri Vain; Hayretdin Bahsi

doi:10.1007/978-3-030-64991-3_6

Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System

Leonidas Tsiopoulos, Alar Kuusik, Jüri Vain, Hayretdin Bahsi

Information Technology

Research output: Chapter in Book/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

Pacemakers’ safety, security and reliability are of utmost importance for patient’s life quality in various daily situations. An integral characteristic of the pacemaker that depends on all of these attributes is its lifetime. In current medical practice the pacemaker’s expected lifetime is estimated relying on manufacturer’s data sheet and expert knowledge that may result in quite rough approximations if patient’s specifics are not taken into account. In this paper we perform a model-based quantitative analysis of pacemaker lifetime that takes into account patient specific factors, including general health condition, acting environment, remote reporting and others. We demonstrate that including these factors in analysis can provide drastically different results compared to that of average approximating estimates.

Original language	English
Title of host publication	Body Area Networks
Subtitle of host publication	Smart IoT and Big Data for Intelligent Health
Publisher	Springer
Pages	77-91
ISBN (Print)	978-3-030-64990-6
DOIs	https://doi.org/10.1007/978-3-030-64991-3_6
Publication status	Published - 2020
MoE publication type	A4 Article in a conference publication
Event	15th EAI International Conference, BODYNETS 2020 - Duration: 21 Oct 2020 → …

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series

Conference

Conference	15th EAI International Conference, BODYNETS 2020
Period	21/10/20 → …

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10.1007/978-3-030-64991-3_6

Cite this

Tsiopoulos, L., Kuusik, A., Vain, J., & Bahsi, H. (2020). Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System. In Body Area Networks: Smart IoT and Big Data for Intelligent Health (pp. 77-91). (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series). Springer. https://doi.org/10.1007/978-3-030-64991-3_6

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title = "Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System",

abstract = "Pacemakers{\textquoteright} safety, security and reliability are of utmost importance for patient{\textquoteright}s life quality in various daily situations. An integral characteristic of the pacemaker that depends on all of these attributes is its lifetime. In current medical practice the pacemaker{\textquoteright}s expected lifetime is estimated relying on manufacturer{\textquoteright}s data sheet and expert knowledge that may result in quite rough approximations if patient{\textquoteright}s specifics are not taken into account. In this paper we perform a model-based quantitative analysis of pacemaker lifetime that takes into account patient specific factors, including general health condition, acting environment, remote reporting and others. We demonstrate that including these factors in analysis can provide drastically different results compared to that of average approximating estimates.",

author = "Leonidas Tsiopoulos and Alar Kuusik and J{\"u}ri Vain and Hayretdin Bahsi",

year = "2020",

doi = "10.1007/978-3-030-64991-3_6",

language = "English",

isbn = "978-3-030-64990-6",

series = "Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series",

publisher = "Springer",

pages = "77--91",

booktitle = "Body Area Networks",

note = "15th EAI International Conference, BODYNETS 2020 ; Conference date: 21-10-2020",

}

Tsiopoulos, L, Kuusik, A, Vain, J & Bahsi, H 2020, Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System. in Body Area Networks: Smart IoT and Big Data for Intelligent Health. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series, Springer, pp. 77-91, 15th EAI International Conference, BODYNETS 2020, 21/10/20. https://doi.org/10.1007/978-3-030-64991-3_6

Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System. / Tsiopoulos, Leonidas; Kuusik, Alar; Vain, Jüri et al.
Body Area Networks: Smart IoT and Big Data for Intelligent Health. Springer, 2020. p. 77-91 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series).

Research output: Chapter in Book/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System

AU - Tsiopoulos, Leonidas

AU - Kuusik, Alar

AU - Vain, Jüri

AU - Bahsi, Hayretdin

PY - 2020

Y1 - 2020

N2 - Pacemakers’ safety, security and reliability are of utmost importance for patient’s life quality in various daily situations. An integral characteristic of the pacemaker that depends on all of these attributes is its lifetime. In current medical practice the pacemaker’s expected lifetime is estimated relying on manufacturer’s data sheet and expert knowledge that may result in quite rough approximations if patient’s specifics are not taken into account. In this paper we perform a model-based quantitative analysis of pacemaker lifetime that takes into account patient specific factors, including general health condition, acting environment, remote reporting and others. We demonstrate that including these factors in analysis can provide drastically different results compared to that of average approximating estimates.

AB - Pacemakers’ safety, security and reliability are of utmost importance for patient’s life quality in various daily situations. An integral characteristic of the pacemaker that depends on all of these attributes is its lifetime. In current medical practice the pacemaker’s expected lifetime is estimated relying on manufacturer’s data sheet and expert knowledge that may result in quite rough approximations if patient’s specifics are not taken into account. In this paper we perform a model-based quantitative analysis of pacemaker lifetime that takes into account patient specific factors, including general health condition, acting environment, remote reporting and others. We demonstrate that including these factors in analysis can provide drastically different results compared to that of average approximating estimates.

U2 - 10.1007/978-3-030-64991-3_6

DO - 10.1007/978-3-030-64991-3_6

M3 - Conference contribution

SN - 978-3-030-64990-6

T3 - Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series

SP - 77

EP - 91

BT - Body Area Networks

PB - Springer

T2 - 15th EAI International Conference, BODYNETS 2020

Y2 - 21 October 2020

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Tsiopoulos L, Kuusik A, Vain J, Bahsi H. Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System. In Body Area Networks: Smart IoT and Big Data for Intelligent Health. Springer. 2020. p. 77-91. (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series). doi: 10.1007/978-3-030-64991-3_6

Model-Based Analysis of Secure and Patient-Dependent Pacemaker Monitoring System

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